引言 亲爱的新老朋友们，新春佳节之际，先给大家拜个早年，祝大家新的一年工作顺利，万事如意！ 幸福团圆 · 喜迎年味在这举家团圆的日子里，我们也带给大家一个好消息，AI-structure Copilot再次突破创新，全新功能上线——建筑平面布置，为您的设计工作带来全新的便捷与高效！该功能可根据用户给定的建筑外轮廓和房间数量的需求，智能生成合理的平面布置方案，旨在帮助设计师快速完成初步设计，大幅提升工作效率。我们的建筑平面布置产品包括“HouseMind：建筑户型平面生成与编辑平台”和“ChatHouseDiffusion：建筑户型平面生成与3D展示平台”两套全新算法。本期将介绍“HouseMind：建筑户型平面生成与编辑平台”，下一期内容将聚焦于“建筑户型平面生成与3D展示平台”。 1. "HouseMind：建筑户型平面生成与编辑平台"上线 官网 (https:// ai-structure.com/#/IntelligentDesignLabs) 已上线新产品——HouseMind：建筑户型平面生成与编辑平台（图1）。该产品专注于建筑户型空间的智能化划分，融合了大语言模型（LLM）等前沿技术，辅助建筑师实现对平面布局的深度理解、自动生成与精准编辑。 图1 建筑户型平面生成与编辑平台“建筑户型平面生成与编辑平台”基于用户提供的建筑轮廓及设计需求，系统能够自动完成卧室、起居室、厨房及卫生间等功能房间的合理规划与排布。同时，它支持根据用户指令进行交互式修改，帮助设计师快速推敲户型方案，显著提升方案设计阶段的工作效率。 2. HouseMind 使用介绍 2.1 软件界面介绍 “建筑户型平面生成与编辑平台”系统界面主要分为系统工具栏、顶部工具栏、可视化工作区、逻辑编辑区和对话交互区五个部分，如图2所示。 图2 操作界面（1）系统工具栏：可切换语言（中文/English）和主题颜色（黑夜/白天）。（2）顶部工具栏：可通过左侧“生成”和“编辑”两个主要选项卡进行功能模式切换；同时，可通过右侧功能按键完成上传图片、手动绘制外轮廓（按照网格捕捉进行正交绘制）、载入示例和下载文件等操作。（3）可视化工作区：用于显示当前的户型轮廓或生成的平面图，默认框定范围为14米×14米。（4）逻辑编辑区：用于用户进行房间数量、功能、面积和逻辑关系等的设置，逻辑关系越清晰准确，生成的效果越好。其中，关系气泡图以可视化气泡形式展示房间及其连接关系，用户可以拖动房间位置来设置和调整房间之间的关系；房间列表可以详细设置每个房间的类型、面积和方位。（5）对话交互区：用户可以输入自然语言指令，与 AI 进行交互。 2.2 设定建筑外轮廓 用户可以通过两种方式设定建筑外轮廓，如图3所示。方法一：用户点击 “绘制外轮廓” 按钮，在左侧画布上点击鼠标定点，绘制封闭的多边形。方法二：用户点击 “上传图片” 或直接拖拽一张黑色轮廓图到画布区域。 （a）绘制外轮廓 （b）上传图片图3 设定建筑外轮廓 2.3 指定房间数量和连通关系 用户可以在逻辑编辑区添加房间，设定房间连接关系，并设定房间方位和大小，如图4所示。在这里分别设置了客厅、餐厅、主卧、次卧、厨房和卫生间六个房间类型。同时，用户可通过关系气泡图，利用”添加连接“和”删除连接“功能设置各个房间的连通关系。 图4 指定房间数量和连通关系 2.4 平面布置生成 用户完成建筑外轮廓设定、房间数量和连通关系设定后，点击发送按钮，即可完成建筑平面布置的生成，如图5所示。 图5 建筑平面布置生成 2.5 根据用户需求调整房间布局 在完成平面布置生成后，用户可根据实际需要，通过“对话交互区”和“逻辑编辑区”对生成结果进行调整，通过调整得到符合自己要求的平面布局。比如，针对图5已经生成的平面布置，首先点击同步气泡图，获取当前布局的拓扑关系，然后可以通过下面两种方式指挥AI开展工作，如图6所示。调整方式一（整体修改）：保持“生成”模式，在右侧列表中修改房间属性（如将“次卧”改为“书房”，将“厨房”面积改小），或在气泡图中增删连线。调整方式二（局部修改）：点击“编辑”按钮进入编辑模式，在右侧列表中修改房间属性或在底部输入指令。 （a）通过“逻辑编辑区”整体修改设计结果 （b）通过“对话交互区”局部修改生成结果图6 根据用户需求调整房间布局 结语 AI-structure Copilot新增建筑平面智能设计功能，旨在帮助您高效完成建筑平面布置。我们诚邀各位用户访问官网进行试用！后续，我们还将不断完善相关产品功能。欢迎大家持续关注我们的工作，多多支持！温馨提示：为更好地使用AI设计工具，请仔细阅读使用说明书相关论文Liao WJ, Lu XZ, Huang YL, Zheng Z, Lin YQ, Automated structural design of shear wall residential buildings using generative adversarial networks, Automation in Construction, 2021, 132: 103931. DOI: 10.1016/j.autcon.2021.103931.Lu XZ, Liao WJ, Zhang Y, Huang YL, Intelligent structural design of shear wall residence using physics-enhanced generative adversarial networks, Earthquake Engineering & Structural Dynamics, 2022, 51(7): 1657-1676. DOI: 10.1002/eqe.3632.Zhao PJ, Liao WJ, Xue HJ, Lu XZ, Intelligent design method for beam and slab of shear wall structure based on deep learning, Journal of Building Engineering, 2022, 57: 104838. DOI: 10.1016/j.jobe.2022.104838.Liao WJ, Huang YL, Zheng Z, Lu XZ, Intelligent generative structural design method for shear-wall building based on “fused-text-image-to-image” generative adversarial networks, Expert Systems with Applications, 2022, 118530, DOI: 10.1016/j.eswa.2022.118530.Fei YF, Liao WJ, Zhang S, Yin PF, Han B, Zhao PJ, Chen XY, Lu XZ, Integrated schematic design method for shear wall structures: a practical application of generative adversarial networks, Buildings, 2022, 12(9): 1295. DOI: 10.3390/buildings1209129.Fei YF, Liao WJ, Huang YL, Lu XZ, Knowledge-enhanced generative adversarial networks for schematic design of framed tube structures, Automation in Construction, 2022, 144: 104619. DOI: 10.1016/j.autcon.2022.104619.Zhao PJ, Liao WJ, Huang YL, Lu XZ, Intelligent design of shear wall layout based on attention-enhanced generative adversarial network, Engineering Structures, 2023, 274: 115170. DOI: 10.1016/j.engstruct.2022.115170.Zhao PJ, Liao WJ, Huang YL, Lu XZ, Intelligent beam layout design for frame structure based on graph neural networks, Journal of Building Engineering, 2023, 63, Part A: 105499. DOI: 10.1016/j.jobe.2022.105499.Zhao PJ, Liao WJ, Huang YL, Lu XZ, Intelligent design of shear wall layout based on graph neural networks, Advanced Engineering Informatics, 2023, 55:101886, DOI: 10.1016/j.aei.2023.101886Liao WJ, Wang XY, Fei YF, Huang YL, Xie LL, Lu XZ, Base-isolation design of shear wall structures using physics-rule-co-guided self-supervised generative adversarial networks, Earthquake Engineering & Structural Dynamics, 2023, 52(11): 3281-3303. DOI:10.1002/eqe.3862.Feng YT, Fei YF, Lin YQ, Liao WJ, Lu XZ, Intelligent generative design for shear wall cross-sectional size using rule-embedded generative adversarial network, Journal of Structural Engineering-ASCE, 2023, 149(11). 04023161. DOI:10.1061/JSENDH.STENG-12206.Fei YF, Liao WJ, Lu XZ, Guan H, Knowledge-enhanced graph neural networks for construction material quantity estimation of reinforced concrete buildings, Computer-Aided Civil and Infrastructure Engineering, 2024, 39(4): 518-538. DOI: 10.1111/mice.13094.Zhao PJ, Fei YF, Huang YL, Feng YT, Liao WJ, Lu XZ, Design-condition-informed shear wall layout design based on graph neural networks, Advanced Engineering Informatics, 2023, 58: 102190. DOI: 10.1016/j.aei.2023.102190.Fei YF, Liao WJ, Lu XZ, Taciroglu E, Guan H, Semi-supervised learning method incorporating structural optimization for shear-wall structure design using s mall and long-tailed datasets, Journal of Building Engineering, 2023, 79: 107873. DOI：10.1016/j.jobe.2023.107873Liao WJ, Lu XZ, Fei YF, Gu Y, Huang YL, Generative AI design for building structures, Automation in Construction, 2024, 157: 105187. DOI: 10.1016/j.autcon.2023.105187Zhao PJ, Liao WJ, Huang YL, Lu XZ, Beam layout design of shear wall structures based on graph neural networks, Automation in Construction, 2024, 158: 105223. DOI: 10.1016/j.autcon.2023.105223Qin SZ, Liao WJ, Huang SN, Hu KG, Tan Z, Gao Y, Lu XZ, AIstructure-Copilot: assistant for generative AI-driven intelligent design of building structures, S mart Construction, 2024, DOI: 10.55092/sc20240001Gu Y, Huang YL, Liao WJ, Lu XZ, Intelligent design of shear wall layout based on diffusion models, Computer-Aided Civil and Infrastructure Engineering, 2024, 39(23):3610-3625. DOI: 10.1111/mice.13236Fei YF, Liao WJ, Zhao PJ, Lu X*, Guan H, Hybrid surrogate model combining physics and data for seis mic drift estimation of shear-wall structures, Earthquake Engineering & Structural Dynamics, 2024, 53(10): 3093-3112. DOI: 10.1002/eqe.4151Han J, Lu XZ, Gu Y, Cai Q, Xue HJ, Liao WJ, Optimized data representation and understanding method for the intelligent design of shear wall structures, Engineering Structures, 2024, 315: 118500. DOI: 10.1016/j.engstruct.2024.118500Qin SZ, Guan H, Liao WJ, Gu Y, Zheng Z, Xue HJ, Lu XZ, Intelligent design and optimization system for shear wall structures based on large language models and generative artificial intelligence, Journal of Building Engineering, 2024, 95: 109996. DOI: 10.1016/j.jobe.2024.109996Wang ZH, Yue Y, Chen Y, Liao WJ, Li CS, Hu KG, Tan Z, Lu XZ. Expert experience-embedded evaluation and decision-making method for intelligent design of shear wall structures. Journal of Computing in Civil Engineering-ASCE, 2025, 39(1). DOI: 10.1061/JCCEE5.CPENG-6076Tan Z, Qin SZ, Hu KG, Liao WJ, Gao Y, Lu XZ, Intelligent generation and optimization method for the retrofit design of RC frame structures using buckling-restrained braces, Earthquake Engineering & Structural Dynamics, 2025, 54(2): 530-547. DOI: 10.1002/eqe.4268Yu Y, Chen Y, Liao WJ, Wang ZH, Zhang SL, Kang YJ, Lu XZ, Intelligent generation and interpretability ana lysis of shear wall structure design by learning from multidimensional to high-dimensional features, Engineering Structures, 2025, 325: 119472. DOI: 10.1016/j.engstruct.2024.119472Qin SZ, Liao WJ, Huang YL, Zhang Shulu, Gu Y, Han J, Lu XZ, Intelligent design for component size generation in reinforced concrete frame structures using heterogeneous graph neural networks, Automation in Construction, 2025, 171: 105967. Xia JK, Liao WJ, Han B, Zhang SL, Lu XZ, Intelligent co-design of shear wall and beam layouts using a graph neural network, Automation in Construction, 2025, 172: 106024. Qin SZ, Liao WJ, Tan Z, Hu KG, Gao Y, Lu XZ, Comparative ana lysis of intelligent retrofit design methods of RC frame structures using buckling-restrained braces. Bulletin of Earthquake Engineering, 2025, DOI: 10.1007/s10518-025-02164-3Liao WJ, Zhang ZL, Liu B, Lu XZ, Liu DF, Liu Q, Duan ZJ, Liu C, Intelligent zoning design of concrete-faced rockfill dams using image-parameter fusion enhanced generative adversarial networks, Engineering Structures, 2025, 339: 120662. DOI: 10.1016/j.engstruct.2025.120662Qin SZ, Fei YF, Liao WJ, Lu XZ*, Leveraging data-driven artificial intelligence in optimization design for building structures: A review, Engineering Structures, 2025, 341: 120810. DOI: 10.1016/j.engstruct.2025.120810Fei YF, Lu XZ, Liao WJ, Guan H, Data enhancement for generative AI design of shear wall structures incorporating structural optimization and diffusion models, Advances in Structural Engineering, 2025, DOI: 10.1177/13694332251353614Gu Y, Qin SZ, Liao WJ, Lu XZ*, Intelligent design of dimensions of reinforced concrete frame structure components using diffusion models, Computers in Industry, 2026, 175: 104428. DOI: 10.1016/j.compind.2025.104428 来源：陆新征课题组
